Whitening of data-dependent, non-stationary noise in an inter-symbol interference channel detector

ABSTRACT

A decoder includes cascaded lattice filters that receive encoded data and include adaptive inputs and output taps. A tap control couples a selected output tap to a viterbi input as a function of a viterbi output. A noise adaptation circuit provides adjustment to the adaptive inputs as a function of the viterbi output to whiten non-stationary noise that is received with the encoded data.

FIELD OF THE INVENTION

The present invention relates generally to data detection incommunication channels subject to inter-symbol interference (ISI), andmore particularly but not by limitation to detectors that are subject todata-dependent, nonstationary noise.

BACKGROUND OF THE INVENTION

Data communication detectors are used in read channels of disc drives.State of the art detectors employ Data-Dependent Noise Whitening (DDNW)metrics, either in the branch metrics of a Viterbi detector, or in apost-processor that effectively ‘corrects’ decisions made by a non-DDNWmetric Viterbi. The data-dependent noise whitening process isaccomplished with a finite-impulse response (FIR) discrete time filter,implemented in hardware as a transversal filter structure.

The required data-dependent transversal filter coefficients for noisewhitening are estimated or adapted using a Least Means Squared (LMS)algorithm. The LMS algorithm used with a transversal filter structure,however, has slow filter convergence, especially when the filter inputcorrelation matrix has a large eigenvalue spread, such as occurs withhigh density magnetic recording. In addition, a digital transversalfilter implementation requires a priori fixed range and resolution ofthe data-dependent coefficients for finite precision representation.However, since each transversal filter coefficient must be allowed totake a different value for each data pattern considered, there is inpractice no way to know beforehand how to optimally choose finiteprecision range and resolution for this structure.

The transversal structure also does not allow for efficientorder-decoupling or modularity. In other words, if the optimal Lth orderwhitening transversal filter has been calculated, one must re-calculatethe values of all filter coefficients in order to achieve the optimal(L+1)th order filter. Each time the order of the filter changes, thereis a requirement to recalculate the values of all filter coefficients.The transversal filters are not modular filters.

A noise whitening filter structure is needed that provides efficientwhitening of data-dependent noise for the purpose of data detection overinter-symbol interference channels without suffering the disadvantagesinherent in the transversal structure. Embodiments of the presentinvention provide solutions to these and other problems, and offer otheradvantages over the prior art.

SUMMARY OF THE INVENTION

Disclosed is a decoder that comprises cascaded lattice filters. Thecascaded lattice filters receive encoded data. The cascaded latticefilters include adaptive inputs and output taps. The decoder alsocomprises a Viterbi path memory unit and survival register unit circuitwith a Viterbi input and a Viterbi output.

The decoder includes a tap control. The tap control couples a selectedoutput tap to the Viterbi input as a function of the Viterbi output. Thedecoder includes a noise adaptation circuit. The noise adaptationcircuit provides adjustment to the adaptive inputs as a function of theViterbi output to whiten non-stationary noise that is received with theencoded data.

Other features and benefits that characterize embodiments of the presentinvention will be apparent upon reading the following detaileddescription and review of the associated drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an isometric view of a disc drive.

FIG. 2 illustrates a communication channel.

FIG. 3 illustrates a lattice filter stage.

FIG. 4A illustrates an adaptive lattice circuit in an operating mode.

FIG. 4B illustrates the adaptive lattice circuit of FIG. 4A in atraining mode.

FIG. 5A illustrates the cascaded lattice filter of FIG. 4A in a“stacked” direction relative to FIG. 4A.

FIG. 5B illustrates a trellis state diagram for the cascaded latticefilter of FIG. 4A.

FIG. 6 illustrates a block diagram of a disc drive.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Some physical communication channels for transmission of digital dataare subject to non-stationary noise, which is difficult for aconventional Viterbi detector to correct, where each trellis branch, ortransition, represents a noiseless value conditioned on a hypothesizedbinary data sequence. In practice, however, there is a special class ofnon-stationary noise referred to as ‘data-dependent’ noise.Data-dependent noise appears statistically stationary when conditionedon the transmission of certain data-sequences, and therefore aconventional Viterbi detector can be augmented such that the branchmetric for a given trellis branch is conditioned on a noiseless value,and the data-dependent noise statistics associated with the giventransition. In the embodiments described below, cascaded multistagelattice filters are utilized to accomplish the required data-dependentnoise whitening (DDNW) operation that is inherent in DDNW-metric Viterbidetection. The order-decoupling property of lattice filter structures isexploited to allow for independent adaptation of each lattice structure,and also to allow for an overall detector that can dynamically add ordelete lattice stages to efficiently trade off between detectioncapability and associated circuit power consumption.

The detection comprises multiple cascaded lattice filter stages in thepath metric of a Viterbi-like detector. Each individual cascaded latticefilter comprises multiple lattice filter stages, where an individuallattice filter stage is defined by a single filter coefficient. Inaddition, each lattice filter stage implements a unique Lth orderdata-dependent whitening filter for the data dependent noise associateda Viterbi trellis branch. Each data-dependent lattice whitening filterreceives data-symbol rate samples that have been equalized by afront-end FIR filter to a specific partial response target.

The cascaded lattice filters include adaptive inputs and output taps foreach lattice stage. The detector includes a tap control. The tap controlcouples a selected lattice stage output tap to the Viterbi path metricunit.

The detector includes a decision-directed noise adaptation circuit. Thenoise adaptation circuit provides adjustment to the adaptive inputs ofthe lattice filter selected as a function of the Viterbi output, andthus adaptively optimizes the lattice filter coefficients so as towhiten non-stationary noise that is received with the equalizedsymbol-rate data. The arrangement can be used, for example in a readchannel of a disc drive such as the one illustrated in FIG. 1.

FIG. 1 is an isometric view of a disc drive 100 in which embodiments ofthe present invention are useful. Disc drive 100 includes a housing witha base 102 and a top cover (not shown). Disc drive 100 further includesa disc pack 106, which is mounted on a spindle motor (not shown) by adisc clamp 108. Disc pack 106 includes a plurality of individual discs,which are mounted for co-rotation about central axis 109 in a directionindicated by arrow 107. Each disc surface has an associated disc headslider 110 which is mounted to disc drive 100 for communication with thedisc surface. In the example shown in FIG. 1, sliders 110 are supportedby suspensions 112 which are in turn attached to track accessing arms114 of an actuator 116. The actuator shown in FIG. 1 is of the typeknown as a rotary moving coil actuator and includes a voice coil motor(VCM), shown generally at 118. Voice coil motor 118 rotates actuator 116with its attached heads 110 about a pivot shaft 120 to position heads110 over a desired data track along an arcuate path 122 between a discinner diameter 124 and a disc outer diameter 126. Voice coil motor 118is driven by electronics 130 based on signals generated by heads 110 anda host computer (not shown). Electronics 130 includes an encoder and adecoder for data stored on the data tracks. The disc drive 100 comprisesone example of data communication channel. Another example of acommunication channel is described below in connection with FIG. 2.

FIG. 2 illustrates a communication channel that receives binary data in204 and provides data out 244. The communication channel 200 isadaptable to a wide variety of communication applications. Channel 200is subject to transmission errors due to the presence of non-stationarynoise 202 introduced in a physical communication medium 203. The term“non-stationary noise” as used in this application means a noise forwhich the first and second order statistics vary as a function of time.

In an example of a disc drive read/write channel, for example, first andsecond order statistics can vary by location on the magnetic media of adisk drive. One example of data-dependent non-stationary noise is themedia noise that exists only at the boundary of magnetic mediatransitions, e.g. flux reversals in saturation recording. Written datasequences that result in a long run of no transitions result in readbackwaveforms that exhibit essentially no media noise.

In another example, multipath fading in a digital radio link includespropagation path variations that result in non-stationary noise in areceived digital radio signal. Additionally, any digital pulse-amplitudemodulation (PAM) method that suffers from clock jitter will yieldreceived waveforms with data-dependent, non-stationary noisecontributions.

In FIG. 2, an encoder 206 receives the input binary data b_(k) 204 thatis not encoded for transmission over the physical medium 203. Theencoder 206 provides encoded data a_(k) 208 to a PAM modulationoperation 210. An example of an encoder 206 is a block code thatprevents long runs of binary 0's or 1's to facilitate timing or phaserecovery operations at the receiver. The PAM modulator 210 converts theencoded binary data a_(k) 208 into a sequence of analog waveforms 212suitable for transmission through the medium 203 (for instance, in amagnetic recording example, the modulation operation 210 represents thegeneration of a write current used to saturate the magnetic media in onedirection or another). In another example, the combination of modulator210 and transmission medium 203 comprises a radio transmitter, and radiopropagation through the atmosphere. A received, noisy, analog waveform214 is subsequently processed by an analog front-end 216 whichconditions the analog signal by analog filtering, preamplification, andextraction of a discrete-time, symbol-rate clock, noisy signal 215. Thesymbol-rate, discrete-time signal 215 is equalized with an FIR filter219 so that a reduced noise signal portion of the FIR output, Y_(K) 218has a known, limited-extent, intersymbol interference (ISI) structure.The equalization process in the FIR equalizer 219 will typically resultin adding statistical correlation to the data-dependent noise portion ofY_(K) 218. In each example of modulation/medium transmission, thereceived, equalized, discrete-time signal 218 includes the effects ofintersymbol interference, and data-dependent, correlated, non-stationarynoise. An example of a signal processing path that produces a filtered,equalized signal Y_(k) is described in more detail below in connectionwith FIG. 6.

The equalized signal Y_(K) at 218 couples to an input 222 of multiplecascaded lattice whitening filters 232 in the detector 220. The multiplecascaded lattice whitening filters are illustrated in a stacked fashionin FIG. 2. The cascaded lattice filters 232 are utilized as part of thebranch metric unit (BMU) operation for a Viterbi detector, and includeadaptive inputs 224 that adjust cascaded lattice filter coefficients(reflection coefficients as described in more detail below in connectionwith FIG. 3). The cascaded lattice filters 232 include output stage taps226 that provide outputs of successive individual lattice filter stages.A noise adaptation circuit 230 generates the adaptive coefficientupdates 224 in a training mode. A lattice stage tap control 228 is usedto statically or dynamically choose which stage of the lattice isrequired for an appropriate trade off between detection capability, andcircuit power. The stage tap control 228 could thus be set by a registerexisting to communicate to the read channel (static), or elseautomatically ‘stop’ at a lattice stage with a coefficient <<1 inmagnitude (automatic).

As part of the BMU operation, the cascaded lattice filters 232 perform adata-dependent whitening process on the input Y_(K) 218 for each of the2^(N+1) possible trellis transition sequences T_(k)=[a_(k−N), a_(k−N+1),. . . , a_(k−1), a_(k)] represented by a trellis branch in a 2^(N) stateViterbi algorithm.

There are 2^(N+1) sets of lattice whitening filters (such as latticewhitening filters 304 in FIG. 5A) for the specific example of N=2, alongwith a portion of the corresponding 4-state Viterbi trellis (such astrellis 308 in FIG. 5B). In this case, each transition (represented byan arrow) from a trellis state at time K to a trellis state at time K+1corresponds to a unique noiseless value, and also to a unique latticewhitening filter 304. The lattice filter coefficients corresponding to agiven data-dependent transition T_(k) are determined by the second orderdata-dependent noise statistics, conditioned on T_(k).

The detector 220 includes a Viterbi path memory unit (PMU) and survivalregister unit (SRU) 234 used to keep track of the most likely binarydata sequence represented by the Viterbi output â_(k) 240. The PMU/SRUunit includes a memory 235 which can be a shift register, a RAM, orother form of memory. The memory 235 receives a stream of outputs â_(k)240 and produces the output {circumflex over (T)}_(K). In turn, theestimated data sequence 240 is concatenated to form the estimatedtrellis transition sequence ({circumflex over (T)}_(K)) used to selectwhich of the possible 2^(N+1) sets of lattice whitening filtercoefficients should be adapted.

Adjustment of the adaptive inputs 224 to the cascaded lattice filters232 is order-decoupled, or in other words modular. The adjustment of anadaptive coefficient by adaptive inputs 224 on a particular latticefilter stage (in the cascaded lattice filters 232) is independent of theadjustment the following stages in the cascade. Two immediate benefitsof this modularity are:

1. Adaptation of lattice coefficients can be performed one stage at atime, without loss of optimality, thus increasing convergence time, anddecreasing the required adaptive circuitry.

2. In contrast to transversal filter structures, lattice stages can beincreased to obtain better detection capability, or decreased to save oncomplexity and power consumption, without the need to recalculate allfilter coefficients.

The Viterbi output (â_(K)) represents the maximum-likelihood estimate ofa_(k) for an ISI channel in the presence of data-dependent, Gauss-Markovnoise. The modulation decoder 242 recovers an estimate ({circumflex over(b)}_(K)) 244 of the original data sequence (b_(K)) 204, and can eitherbe sent for further error control decoding, or formatted andresynchronized for use with a host system such as a computer.

The arrangement shown in FIG. 2. avoids the use of transversalstructures in the BMU for data-dependent noise whitening, which aretypically adapted with a least-mean-square (LMS) algorithm. Note thatfor optimal convergence speed of transversal filters, the LMS algorithmmust be applied simultaneously to all transversal filter coefficients,and is also known to suffer slow convergence when the filter inputcorrelation matrix has a large eigenvalue spread, a condition common inhigh-density magnetic recording. Furthermore, transversal whiteningfilter coefficient representation in finite precision for digitalimplementation is not straightforward because a priori bounds on thecoefficient ranges are unknown.

With the use of the lattice filter, the magnitude of each reflectioncoefficient is always less than or equal to one. With the use of latticefilters, finite precision implementation can be made more accuratelythan with the transversal structure. An example of a single latticefilter stage (within one of cascaded lattice filters) is described inmore detail below in connection with FIG. 3. An example of cascadedlattice filters, a noise adaptation circuit and tap control aredescribed in more detail below in connection with FIGS. 4A, 4B.

FIG. 3 illustrates a lattice filter, also called a lattice filter stage,400. The lattice filter 400 includes first and second inputs 402, 404 ata left side, and first and second outputs 406, 408 at a right side. Thelattice filter stage 400 has a first signal processing path 410 thatruns along a straight horizontal line that extends from the first input402 through a summing junction 412 to the first output 406. The latticefilter stage 400 has a second signal processing path 414 that runs alonga straight horizontal line that extends from the second input 404through a delay element 416 and a summing junction 418 to the secondoutput 408. The lattice filter stage 400 has a second signal processingpath 414 that runs along a straight horizontal line that extends fromthe second input 404 through a delay element 416 and a summing junction418 to the second output 408.

The lattice filter stage 400 has a first lattice (crossover) signalprocessing path 420 that serves to bridge signals derived from the firstinput 402 to the second output 408. The lattice filter stage 400 has asecond lattice (crossover) signal processing path 422 that serves tobridge signals derived from the second input 404 to the first output406. The lattice (crossover) topology shown in FIG. 4 can also bedepicted as an equivalent bridge network with inputs on one set ofopposite bridge nodes and outputs on another set of opposite bridgenodes (not shown).

The second input 404 couples to the delay element 416. The delay element416 provides a delayed output 430 to the summing junction 418 and to aprocessor 432 in the second lattice path 422. The processor 432 has areflection coefficient 434 that is adjusted by an adaptive input 436.The processor 432 provides a processor output 438 to the summingjunction 412. The summing junction 412 sums the processor output 438 andthe first input 402. The summing junction 412 generates the first output406. Adjustment of the reflection coefficients is independent of theoutput tap selected by the tap control.

The first input 402 couples to a processor 440. The processor 440 has areflection coefficient 442 that is adjusted by the adaptive input 436.The processor 440 provides a processor output 444 to the summingjunction 418. The summing junction 418 sums the processor output 444 andthe delayed output 430. The summing junction 418 provides the secondoutput 408. A cascaded series of lattice filters such as lattice filter400 is described below in connection with FIG. 5.

The term “reflection coefficient” refers to a processor gain that isless than or equal to one in magnitude for both processors 432, 440.Both processors 432, 440 in a given lattice filter stage preferably haveidentical reflection coefficients. The processor gain is a ratio ofprocessor output to processor input.

FIG. 4A illustrates an example of cascaded lattice filters 502 and alattice stage tap select 506 in an operational mode. FIG. 4B illustratesthe same cascaded lattice filters 502 together with a lattice stageadapt select 504 in a training mode. The cascaded lattice filters 502 inFIGS. 4A, 4B comprise lattice filter stages 508, 510, 512, . . . 514that are connected in cascade, i.e., the outputs of one lattice stageare connected to the corresponding inputs of the next subsequent latticestage. Each lattice output stage includes an output tap that connects tothe lattice stage tap select 506 (shown in FIG. 4A).

The lattice stage tap select 506 includes a switch 516 that providesonly one selected output tap at a time on line 518 to a Viterbi input(such as PMU input 238 in FIG. 2). The lattice stage tap select 506includes a lattice stage tap control circuit 520. The lattice stage tapcontrol circuit 520 can be a dynamic or user-programmable (static)control. An example of static control would have the user set the numberof desired stages for each whitening filter via a register on the readchannel. An alternate, dynamic control might sense the reflectioncoefficient magnitude at each stage 508, 510, . . . , 514, and beconfigured to stop at some stage L*, such that reflection coefficientmagnitudes are smaller than some defined threshold for L>L*. As the dataand the output tap selected change over time, there is no need toreadjust adaptive inputs 524, 526, 528, 530 of the cascaded latticefilters because adjustment is independent of the output tap that isselected.

The lattice stage adapt select circuit 504 (FIG. 4B) consecutivelyenables lattice stages, one at a time, from 1=1, 2, . . . L for trainingof the reflection coefficients. In one example of this circuit, asynchronized counter is utilized. The adaptation is made so as tominimize the data-dependent noise n_(k) 540 correlation at the output ofeach lattice stage. The noise sample n_(k) 540 is regenerated in adecision-directed mode by subtracting the noisy, equalized signal Y_(k)544 from a regenerated noiseless sample 542. The regenerated noiselesssample 542 is constructed by filtering Viterbi decisions â_(K) 546 withthe equalized ISI target 548 and delaying this sample by an amount 550determined by the length of the Viterbi survival registers.

The Viterbi decisions (â_(K)) 546 are then concatenated into theappropriate length transition sequence ({circumflex over (T)}_(K)) 552,and this sequence is used by the data dependent filter select 554 toselect which whitening filter is to have its lattice stage adapted.

FIG. 5A illustrates the cascaded lattice filter of FIG. 4A in a“stacked” direction relative to FIG. 4A. As illustrated in FIG. 5A,there are 2^(N+1) sets of cascaded lattice whitening filters 304, 306,308, 310, 312, 314, 316, 318 for the specific example of N=2. Each ofthe stacked whitening filters receives the input 302 Y_(K). Each of thefilters 304, 306, 308, 310, 312, 314, 316, 318 provide an output Z_(K)that, taken together constitute the cascaded filter outputs.

A portion of an exemplary corresponding 4-state Viterbi trellis statediagram 308 is illustrated in FIG. 5B. Each trellis state at times K andK+1 is represented by a circle in FIG. 5B. Each transition (representedby an arrow) from a trellis state at time K to a trellis state at timeK+1 corresponds to a unique noiseless value, and also to a unique one ofthe lattice whitening filters 304-318. The lattice filter coefficientscorresponding to a given data-dependent transition T_(k) are determinedby the second order data-dependent noise statistics, conditioned onT_(k).

FIG. 6 illustrates a block diagram of a disc drive 600. The disc drive600 includes a write channel 602 that receives data from a host (notillustrated). The write channel 602 encodes the data into a multilayerprotocol suitable for writing to a disc, and provides encoded data to ahead 606 for writing on a magnetic storage disc 604 in the disc drive600. The disc drive 600 includes a disc controller 608 that provides acontrol output 610 to a voice coil 612 that positions the head 606. Thedisc controller 608 also provides an electrical drive 614 to a discmotor 616 that spins the disc 604.

The head 606 reads the encoded data written on the disc 604 and couplesthe readback signal along a line 618 to a data input 620 of a readchannel 622. The analog data at data input 620 includes non-stationarynoise due to the writing and reading processes. The read channel 622passes the readback signal through a series of processing blocks thatare arranged in cascade to provide an equalized output Y_(K) at 624. Thecascaded processing blocks in the read channel 622 include apreamplifier 626 that receives input 620, a variable gain amplifier(VGA) 628 that receives a preamplifier output 630, an adjustable lowpass filter 632 that receives a variable gain amplifier output 634, anda finite impulse response (FIR) filter 636 that receives a low passfilter output 638. The FIR filter 636 generates the read channel outputY_(K) at 624 which couples to a Viterbi detector 640. The read channeloutput Y_(K) includes equalized data that is corrupted by non-stationarynoise. The non-stationary noise can be primarily attributed to medianoise of the disc 604. The Viterbi detector 640 includes a Viterbi pathmemory unit (PMU) and survival register unit (SRU) circuit 642 and anadaptive lattice or branch metric unit (BMU) circuit 644. The PMU andSRU circuit 642 generates a Viterbi output 650 that is provided asfeedback to the adaptive lattice circuit 644. Non-stationary noise isused to adjust reflection coefficients in the adaptive lattice circuit644, for example, as described above in connection with FIGS. 2-5. TheViterbi detector 640 can be implemented as shown in FIGS. 5A, 5B forexample. The Viterbi output 650 provides data to a host system (notillustrated). The disc drive 600 thus serves as a communication channelfor storing and reproducing data.

It is to be understood that even though numerous characteristics andadvantages of various embodiments of the invention have been set forthin the foregoing description, together with details of the structure andfunction of various embodiments of the invention, this disclosure isillustrative only, and changes may be made in detail, especially inmatters of structure and arrangement of parts within the principles ofthe present invention to the full extent indicated by the broad generalmeaning of the terms in which the appended claims are expressed. Forexample, the particular elements may vary depending on the particularapplication for the decoder system while maintaining substantially thesame functionality without departing from the scope and spirit of thepresent invention. In addition, although the preferred embodimentsdescribed herein is directed to disc drives and radio systems fordigital data reproduction, it will be appreciated by those skilled inthe art that the teachings of the present invention can be applied toother data storage devices and fiber optic communication, withoutdeparting from the scope and spirit of the present invention.

1. A decoder comprising: cascaded lattice filters that receive encodeddata and that include adaptive inputs and output taps; a Viterbi pathmemory unit and survival register unit circuit with a Viterbi input anda Viterbi output; a tap control coupling a selected output tap from thecascaded lattice filters to the Viterbi input; and a noise adaptationcircuit that provides an adjustment to the adaptive inputs as a functionof an estimated trellis transition sequence to whiten non-stationarynoise.
 2. The decoder of claim 1 wherein the cascaded lattice filtersinclude processors, each processor including a reflection coefficientthat is adjusted by the adjustment.
 3. The decoder of claim 2 whereinthe adjustment of the reflection coefficients is independent of theoutput tap selected by the tap control.
 4. The decoder of claim 2wherein the adjustment comprises a plurality of adjustments for eachcascaded lattice filter, each of the plurality of adjustments beingindependent of one another.
 5. The decoder of claim 1 wherein the noiseadaptation circuit provides the adjustment as a function of past noise.6. The decoder of claim 1 wherein the noise adaptation circuit comprisesa noise detector that generates a noise sample output indicating pastnoise samples in the Viterbi output.
 7. The decoder of claim 1 whereinthe encoded data is received from a communication medium that injectsnon-stationary noise into the encoded data and the selected tap outputprovides data in which the non-stationary noise is whitened.
 8. Thedecoder of claim 1 wherein the Viterbi input has a fixed range, and theViterbi path memory unit and survival register unit circuit has a fixedscale to process the fixed range.
 9. The decoder of claim 1 wherein theViterbi input has a fixed scale and the Viterbi path memory unit andsurvival register unit circuit has a fixed resolution to process thefixed scale.
 10. A method of decoding, comprising: providing encodeddata to cascaded lattice filters that include adaptive inputs and outputtaps; selecting an output tap from the cascaded lattice filters andproviding the selected output tap to a Viterbi input of “a Viterbi pathmemory unit and survival register unit circuit” in order to overcome alack of antecedent basis issue; and providing an adjustment to theadaptive inputs as a function of an estimated trellis transitionsequence to whiten non-stationary noise.
 11. The method of claim 10wherein the cascaded lattice filters include processors with reflectioncoefficients, and: adjusting the reflection coefficients with theadaptive inputs.
 12. The method of claim 11 further comprising:adjusting the reflection coefficients independently from the output tapthat is selected.
 13. The method of claim 11, further comprising:adjusting a reflection coefficient of each cascaded lattice filterindependently from adjustment of the reflection coefficient of othercascaded lattice filters.
 14. The method of claim 10, furthercomprising: providing the adjustment as a function of past noise at theViterbi output.
 15. The method of claim 10, further comprising:providing a noise detector indicating past noise samples in the Viterbioutput.
 16. The method of claim 10, further comprising: receiving theencoded data from a communication medium that injects non-stationarynoise into the encoded data; and providing decoded data at the Viterbiinput with the non-stationary noise whitened.
 17. The method of claim10, further comprising: providing the Viterbi input with a fixed range,and providing the Viterbi path memory unit and survival register unitcircuit with a fixed scale to process the fixed range.
 18. The method ofclaim 10, further comprising: providing the Viterbi input with a fixedscale; and providing the Viterbi path memory unit and survival registerunit circuit with a fixed resolution to process the fixed scale.
 19. Adecoder comprising: cascaded lattice filters that receive encoded dataand that include adaptive inputs and output taps; a Viterbi path memoryunit and survival register unit circuit with a Viterbi input and aViterbi output; means for coupling a selected output tap from thecascaded lattice filters to the Viterbi input; and means for providingan adjustment to the adaptive inputs as a function of an estimatedtrellis transition sequence to whiten non-stationary noise.